This invention relates generally to processing and image reconstruction based on acquired raw image data. In particular, the present invention relates to increasing the processing performance with respect to the image reconstruction of diagnostic image data.
Raw image data from various diagnostic medical systems, such as Computed Tomography (CT) and Positron Emission Tomography (PET) systems, is acquired for diagnostic purposes. The CT and PET systems need to be able to support numerous scanning and reconstruction modes. The associated reconstruction algorithms are complex and computationally intensive. Users of the diagnostic medical systems desire an improvement in image quality, along with minimizing the time required to generate images based on raw image data and improving the reliability of the reconstruction process. By decreasing the amount of time needed to generate the desired images from raw image data, images can be evaluated sooner and patient through-put may be improved.
Previous diagnostic systems used different specialized processing units to accomplish specific tasks. That is, the reconstruction process was broken down according to the steps to be done. The processing units may operate in parallel or serially with respect to each other. In order to add processing capability, however, new processing units had to be added and the system design reconfigured and/or coordinated to integrate the new units and steps, both increasing the complexity and limiting the flexibility of the diagnostic system. Scalability and increased performance are thus difficult to achieve when adding additional processing units.
Thus, an apparatus and method are desired to reconstruct image data that addresses the problems noted above and others previously experienced.